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stats 4th q
21問 • 1年前
  • Joshua Timbol
    • 通報

    問題一覧

  • 1

    describes only the sample

    Statistic

  • 2

    describes an entire population

    Parameter

  • 3

    The simplest way of getting random sample where each member of the population has an equal chance of being chosen as the sample.

    Simple Random Sampling

  • 4

    The population is first divided into separate groups called clusters. Then, a simple random sample of clusters from the available clusters in the population is selected.

    Cluster Random Sampling

  • 5

    This involves selecting a simple random sample from each of a given number of subpopulations proportionally. Each subpopulation is called a stratum (plural: strata).

    Stratified Random Sampling

  • 6

    This involves the random selection of one of the first k • elements in an ordered population, and then the systematic selection of every kth element thereafter.

    1-in-k Kandom Sampling

  • 7

    Two or more probability techniques are combined. It can be described as sampling within the sample.

    Multistage Random Sampling

  • 8

    Probability Techniques

    •Simple Random Sampling •Cluster Random Sampling •Stratified Random Sampling •1-in-k Random Sampling •Multistage Random Sampling

  • 9

    Also called as haphazard sampling. • Carried out on the matter of convenience or ease on the part of the researcher

    Convenience Sampling

  • 10

    Also called as judgmental or selective sampling. • Goal: choose the members of the population which best fitted to answer.

    Purposive Sampling

  • 11

    Also called as chain-referral sampling. • Reason: this is an effective sampling technique when the participants of the study is hard to find.

    Snowball Sampling

  • 12

    Equivalent to stratified random sampling. Example: the population of the study is 30% are single and 70% are married.

    Quota Sampling

  • 13

    Participant or respondents of the study volunteered to participate in the study.

    Volunteer Sampling

  • 14

    This is the probability distribution of the sample mean from all possible samples of a population

    Sampling Distribution of the Sample Mean

  • 15

    This shows how the sample mean varies from sample to sample. This is also called the sampling variability.

    Variance of the Sampling Distribution of the Sample Mean

  • 16

    It is used to measure the accuracy with which the sample represents the population. This is also called the standard error.

    Standard Deviation of the Sampling Distribution of the Sample Mean

  • 17

    implies that as long as the sample size n is sufficiently large, that is, n ≥ 30, the sampling distribution of the sample mean is approximately normal.

    Central Limit Theorem

  • 18

    The mean of the sampling distribution of the sample mean is equal to the population mean.

    Mean of the Sampling Distribution of the Sample Mean

  • 19

    We can determine the percentage that a certain sample has a given sample mean using its __.

    z-score

  • 20

    The appropriate value of n depends on the shape of the population from which the sample is drawn. A good rule of thumb is that the sufficient sample size is n ≥ 30.

    Distribution of the Sampling Distribution of the Sample Mean

  • 21

    Nonprobability Techniques

    •Convenience Sampling •Purposive Sampling •Snowball Sampling •Quota Sampling •Volunteer Sampling

    • Gen Chem

    Gen Chem

    Joshua Timbol · 65問 · 1年前

    Gen Chem

    Gen Chem

    65問 • 1年前
    Joshua Timbol

    pr

    pr

    Joshua Timbol · 36問 · 1年前

    pr

    pr

    36問 • 1年前
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    cpar

    cpar

    Joshua Timbol · 96問 · 2年前

    cpar

    cpar

    96問 • 2年前
    Joshua Timbol

    Cpar(2)

    Cpar(2)

    Joshua Timbol · 40問 · 1年前

    Cpar(2)

    Cpar(2)

    40問 • 1年前
    Joshua Timbol

    cpar lesson 4

    cpar lesson 4

    Joshua Timbol · 17問 · 1年前

    cpar lesson 4

    cpar lesson 4

    17問 • 1年前
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    Mil exam(2)

    Mil exam(2)

    Joshua Timbol · 17問 · 1年前

    Mil exam(2)

    Mil exam(2)

    17問 • 1年前
    Joshua Timbol

    eapp

    eapp

    Joshua Timbol · 40問 · 1年前

    eapp

    eapp

    40問 • 1年前
    Joshua Timbol

    pe

    pe

    Joshua Timbol · 36問 · 1年前

    pe

    pe

    36問 • 1年前
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    kompan

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    Joshua Timbol · 53問 · 1年前

    kompan

    kompan

    53問 • 1年前
    Joshua Timbol

    gen bio 2 4th q

    gen bio 2 4th q

    Joshua Timbol · 44問 · 11ヶ月前

    gen bio 2 4th q

    gen bio 2 4th q

    44問 • 11ヶ月前
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    drrr 3rd q

    Joshua Timbol · 37問 · 1年前

    drrr 3rd q

    drrr 3rd q

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    Work immersion

    Work immersion

    Joshua Timbol · 24問 · 1年前

    Work immersion

    Work immersion

    24問 • 1年前
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    p6 3rd q

    Joshua Timbol · 18問 · 11ヶ月前

    p6 3rd q

    p6 3rd q

    18問 • 11ヶ月前
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    i3 3rd q

    i3 3rd q

    Joshua Timbol · 25問 · 11ヶ月前

    i3 3rd q

    i3 3rd q

    25問 • 11ヶ月前
    Joshua Timbol

    pagpag q1

    pagpag q1

    Joshua Timbol · 44問 · 1年前

    pagpag q1

    pagpag q1

    44問 • 1年前
    Joshua Timbol

    entrep

    entrep

    Joshua Timbol · 42問 · 1年前

    entrep

    entrep

    42問 • 1年前
    Joshua Timbol

    gen bio 2 3rd q

    gen bio 2 3rd q

    Joshua Timbol · 100問 · 11ヶ月前

    gen bio 2 3rd q

    gen bio 2 3rd q

    100問 • 11ヶ月前
    Joshua Timbol

    gen bio 2 3rd q (1)

    gen bio 2 3rd q (1)

    Joshua Timbol · 14問 · 11ヶ月前

    gen bio 2 3rd q (1)

    gen bio 2 3rd q (1)

    14問 • 11ヶ月前
    Joshua Timbol

    gen bio 2

    gen bio 2

    Joshua Timbol · 39問 · 1年前

    gen bio 2

    gen bio 2

    39問 • 1年前
    Joshua Timbol

    Gen chem 2 2nd q

    Gen chem 2 2nd q

    Joshua Timbol · 31問 · 1年前

    Gen chem 2 2nd q

    Gen chem 2 2nd q

    31問 • 1年前
    Joshua Timbol

    問題一覧

  • 1

    describes only the sample

    Statistic

  • 2

    describes an entire population

    Parameter

  • 3

    The simplest way of getting random sample where each member of the population has an equal chance of being chosen as the sample.

    Simple Random Sampling

  • 4

    The population is first divided into separate groups called clusters. Then, a simple random sample of clusters from the available clusters in the population is selected.

    Cluster Random Sampling

  • 5

    This involves selecting a simple random sample from each of a given number of subpopulations proportionally. Each subpopulation is called a stratum (plural: strata).

    Stratified Random Sampling

  • 6

    This involves the random selection of one of the first k • elements in an ordered population, and then the systematic selection of every kth element thereafter.

    1-in-k Kandom Sampling

  • 7

    Two or more probability techniques are combined. It can be described as sampling within the sample.

    Multistage Random Sampling

  • 8

    Probability Techniques

    •Simple Random Sampling •Cluster Random Sampling •Stratified Random Sampling •1-in-k Random Sampling •Multistage Random Sampling

  • 9

    Also called as haphazard sampling. • Carried out on the matter of convenience or ease on the part of the researcher

    Convenience Sampling

  • 10

    Also called as judgmental or selective sampling. • Goal: choose the members of the population which best fitted to answer.

    Purposive Sampling

  • 11

    Also called as chain-referral sampling. • Reason: this is an effective sampling technique when the participants of the study is hard to find.

    Snowball Sampling

  • 12

    Equivalent to stratified random sampling. Example: the population of the study is 30% are single and 70% are married.

    Quota Sampling

  • 13

    Participant or respondents of the study volunteered to participate in the study.

    Volunteer Sampling

  • 14

    This is the probability distribution of the sample mean from all possible samples of a population

    Sampling Distribution of the Sample Mean

  • 15

    This shows how the sample mean varies from sample to sample. This is also called the sampling variability.

    Variance of the Sampling Distribution of the Sample Mean

  • 16

    It is used to measure the accuracy with which the sample represents the population. This is also called the standard error.

    Standard Deviation of the Sampling Distribution of the Sample Mean

  • 17

    implies that as long as the sample size n is sufficiently large, that is, n ≥ 30, the sampling distribution of the sample mean is approximately normal.

    Central Limit Theorem

  • 18

    The mean of the sampling distribution of the sample mean is equal to the population mean.

    Mean of the Sampling Distribution of the Sample Mean

  • 19

    We can determine the percentage that a certain sample has a given sample mean using its __.

    z-score

  • 20

    The appropriate value of n depends on the shape of the population from which the sample is drawn. A good rule of thumb is that the sufficient sample size is n ≥ 30.

    Distribution of the Sampling Distribution of the Sample Mean

  • 21

    Nonprobability Techniques

    •Convenience Sampling •Purposive Sampling •Snowball Sampling •Quota Sampling •Volunteer Sampling